Extracting Semantic Relationships Between Terms from PC Documents and Its Applications to Web Search Personalization
Extracting Semantic Relationships Between Terms from PC Documents and Its Applications to Web Search Personalization
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DOI：
10.1007/11610113_51
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发表时间：
2006-01
期刊：
影响因子：
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通讯作者：
H. Ohshima;S. Oyama;Katsumi Tanaka
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文献类型：
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作者：
H. Ohshima;S. Oyama;Katsumi Tanaka
描述了一种用于提取出现在存储在个人计算机上的文档中的词语之间的语义关系的方法；这些关系可用于个性化网络搜索。它基于这样的假设，即一个人存储在个人计算机上的信息和PC中的目录结构在某种程度上反映了这个人的知识、意识形态和概念分类。它的工作方式是识别PC上文档中的术语之间的语义关系；这些关系反映了个人对成对的每个术语的相对估值。检查目录结构以识别每个目录内的项的外观的偏差。然后，这些偏差被用来识别术语之间的关系。定义了四种关系：广义关系、狭义关系、并存关系和独占关系。例如，它们可用于通过扩展查询和重新排序搜索结果来个性化Web搜索。
A method is described for extracting semantic relationships between terms appearing in documents stored on a personal computer; these relationships can be used to personalize Web search. It is based on the assumption that the information a person stores on a personal computer and the directory structure in the PC reflect, to some extent, the person’s knowledge, ideology, and concept classification. It works by identifying semantic relationships between the terms in documents on the PC; these relationships reflect the person’s relative valuation of each term in a pair. The directory structure is examined to identify the deviations in the appearance of the terms within each directory. These deviations are then used to identify the relationships between the terms. Four relationships are defined: broad, narrow, co-occurrent, and exclusive. They can be used to personalize Web search through, for example, expansion of queries and re-ranking of search results.